This invention relates to automated visual inspection of relative position components. More specifically, the invention relates to machine vision inspection of dual inline package (DIP) switches.
The background of machine vision systems is known. Many systems of optical sensors and comparators of the optical sensor's output are used in industry to inspect or monitor processes or systems of manufacturing. The basic elements of a machine vision system are elements of image acquisition, image processing, data analysis and interface to a user or a host system. Each of these elements is implemented by several technologies or techniques. In a general sense, current machine vision systems have difficulty overcoming the inherent environmental asymmetries in any real process or system. More specifically, it is difficult to resolve process parameters under variable light conditions and variable inspection piece orientations.
There are many types of equipment for each element of a machine vision system. An analog camera or ridicon is a basic technology commonly used in image acquisition. By digitizing a video signal, a digital image is formed. Many of the machine vision systems use solid state cameras. In many instances, the solid state camera is a charged coupled device (CCD) camera that acquires a digital video image of a component to be inspected. Pixel resolution is also a measure of the cameras sensitivity as well as the resolution of the digital processing unit in the image processor. The more sensitive a camera is, the more detail can be captured in the image. This sensitivity can also be a weakness as it can receive erroneous data should a variation in lighting occur.
Another device is a line scan camera (LSC) which only scans in a single line of an image at a time. The LSC uses the motion of a component on an position translation device to move the component beneath the camera to generate the digitized image line by line. The fact that the line scan camera only records a single line of the digital image at any single point in time makes the digital image even more susceptible to light variations and motion perturbations. The intolerance of the line scanning device to variations in a process flow are significant concerns and costs to a process designer that uses a vision system for automated component comparation.
There are a substantial number of methods utilized in designing a vision system for processing of the digitized image. Many image acquisition systems have the ability to provide either a binary black and white image, a grey scale image, or a color image to the image processing system. Each type of image offers advantages and disadvantages to the process designer in designing a visual inspection system. A grey scale image is typically made up of 256 or more levels of resolution per pixel recorded. A standard notation of gray scale levels represents each level in a range from 0 (black) to 255 (white). Color systems are also known.
Image analysis can require that a captured image be identified or related back to a desired or known image. This analysis can include reorientation of the image to be accurately compared to a known quantity. Either the image must be rotated in actual process flow to guarantee that the image is captured in correct orientation; or in post image capture, the part must be rotated via software and compared to a known master image.